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Five billion dollars. That’s the apparent size of Facebook’s latest fine for violating data privacy. 

While many believe the sum is simply a slap on the wrist for a behemoth like Facebook, it’s still the largest amount the Federal Trade Commission has ever levied on a technology company. 

Facebook is clearly still reeling from Cambridge Analytica, after which trust in the company dropped 51%, searches for “delete Facebook” reached 5-year highs, and Facebook’s stock dropped 20%.

While incumbents like Facebook are struggling with their data, startups in highly-regulated, “Third Wave” industries can take advantage by using a data strategy one would least expect: ethics. Beyond complying with regulations, startups that embrace ethics look out for their customers’ best interests, cultivate long-term trust — and avoid billion dollar fines. 

To weave ethics into the very fabric of their business strategies and tech systems, startups should adopt “agile” data governance systems. Often combining law and technology, these systems will become a key weapon of data-centric Third Wave startups to beat incumbents in their field. 

Established, highly-regulated incumbents often use slow and unsystematic data compliance workflows, operated manually by armies of lawyers and technology personnel. Agile data governance systems, in contrast, simplify both these workflows and the use of cutting-edge privacy tools, allowing resource-poor startups both to protect their customers better and to improve their services.

In fact, 47% of customers are willing to switch to startups that protect their sensitive data better. Yet 80% of customers highly value more convenience and better service. 

By using agile data governance, startups can balance protection and improvement. Ultimately, they gain a strategic advantage by obtaining more data, cultivating more loyalty, and being more resilient to inevitable data mishaps. 

Agile data governance helps startups obtain more data — and create more value 

With agile data governance, startups can address their critical weakness: data scarcity. Customers share more data with startups that make data collection a feature, not a burdensome part of the user experience. Agile data governance systems simplify compliance with this data practice. 

Take Ally Bank, which the Ponemon Institute rated as one of the most privacy-protecting banks. In 2017, Ally’s deposits base grew 16%, while those of incumbents declined 4%.

One key principle to its ethical data strategy: minimizing data collection and use. Ally’s customers obtain services through a personalized website, rarely filling out long surveys. When data is requested, it’s done in small doses on the site — and always results in immediate value, such as viewing transactions. 

This is on purpose. Ally’s Chief Marketing Officer publicly calls the industry-mantra of “more data” dangerous to brands and consumers alike.

A critical tool to minimize data use is to use advanced data privacy tools like differential privacy. A favorite of organizations like Apple, differential privacy limits your data analysts’ access to summaries of data, such as averages. And by injecting noise into those summaries, differential privacy creates provable guarantees of privacy and prevents scenarios where malicious parties can reverse-engineer sensitive data. But because differential privacy uses summaries, instead of completely masking the data, companies can still draw meaning from it and improve their services. 

With tools like differential privacy, organizations move beyond governance patterns where data analysts either gain unrestricted access to sensitive data (think: Uber’s controversial “god view”) or face multiple barriers to data access. Instead, startups can use differential privacy to share and pool data safely, helping them overcome data scarcity. The most agile data governance systems allow startups to use differential privacy without code and the large engineering teams that only incumbents can afford.

Ultimately, better data means better predictions — and happier customers.

Agile data governance cultivates customer loyalty

According to Deloitte, 80% of consumers are more loyal to companies they believe protect their data. Yet far fewer leaders at established, incumbent companies — the respondents of the same survey — believed this to be true. Customers care more about their data than the leaders at incumbent companies think. 

This knowledge gap is an opportunity for startups. 

Furthermore, big enterprise companies — themselves customers of many startups — say data compliance risks prevent them from working with startups. And rightly so. Over 80% of data incidents are actually caused by errors from insiders, like third party vendors who mishandle sensitive data by sharing it with inappropriate parties. Yet over 68% of companies do not have good systems to prevent these types of errors. In fact, Facebook’s Cambridge Analytica firestorm — and resulting $ 5 billion fine — was sparked by third party inappropriately sharing personal data with a political consulting firm without user consent. 

As a result, many companies — both startups and incumbents — are holding a ticking time bomb of customer attrition. 

Agile data governance defuses these risks by simplifying the ethical data practices of understanding, controlling, and monitoring data at all times. With such practices, startups can prevent and correct the mishandling of sensitive data quickly.

Cognoa is a good example of a Third Wave healthcare startup adopting these three practices at a rapid pace. First, it understands where all of its sensitive health data lies by connecting all of its databases. Second, Cognoa can control all connected data sources at once from one point by using a single access-and-control layer, as opposed to relying on data silos. When this happens, employees and third parties can only access and share the sensitive data sources they’re supposed to. Finally, data queries are always monitored, allowing Cognoa to produce audit reports frequently and catch problems before they escalate out of control. 

With tools that simplify these three practices, even low-resourced startups can make sure sensitive data is tightly controlled at all times to prevent data incidents. Because key workflows are simplified, these same startups can maintain the speed of their data analytics by sharing data safely with the right parties. With better and safer data sharing across functions, startups can develop the insight necessary to cultivate a loyal fan base for the long-term.

Agile data governance can help startups survive inevitable data incidents

In 2018, Panera mistakenly shared 37 million customer records on its website and took 8 months to respond. Panera’s data incident is a taste of what’s to come: Gartner predicts that 50% of business ethics violations will stem from data incidents like these. In the era of “Big Data,” billion dollar incumbents without agile data governance will likely continue to violate data ethics. 

Given the inevitability of such incidents, startups that adopt agile data governance will likely be the most resilient companies of the future. 

Case in point: Harvard Business Review reports that the stock prices of companies without strong data governance practices drop 150% more than companies that do adopt strong practices. Despite this difference, only 10% of Fortune 500 companies actually employ the data transparency principle identified in the report. Practices include clearly disclosing data practices and giving users control over their privacy settings. 

Sure, data incidents are becoming more common. But that doesn’t mean startups don’t suffer from them. In fact, up to 60% of startups fold after a cyber attack. 

Startups can learn from WebMD, which Deloitte named as one standout in applying data transparency. With a readable privacy policy, customers know how data will be used, helping customers feel comfortable about sharing their data. More informed about the company’s practices, customers are surprised less by incidents. Surprises, BCG found, can reduce consumer spending by one-third. On a self-service platform on WebMD’s site, customers can control their privacy settings and how to share their data, further cultivating trust. 

Self-service tools like WebMD’s are part of agile data governance. These tools allow startups to simplify manual processes, like responding to customer requests to control their data. Instead, startups can focus on safely delivering value to their customers. 

Get ahead of the curve

For so long, the public seemed to care less about their data. 

That’s changing. Senior executives at major companies have been publicly interrogated for not taking data governance seriously. Some, like Facebook and Apple, are even claiming to lead with privacy. Ultimately, data privacy risks significantly rise in Third Wave industries where errors can alter access to key basic needs, such as healthcare, housing, and transportation.

While many incumbents have well-resourced legal and compliance departments, agile data governance goes beyond the “risk mitigation” missions of those functions. Agile governance means that time-consuming and error-prone workflows are streamlined so that companies serve their customers more quickly and safely.

Case in point: even after being advised by an army of lawyers, Zuckerberg’s 30,000-word Senate testimony about Cambridge Analytica included “ethics” only once, and it excluded “data governance” completely.

And even if companies do have legal departments, most don’t make their commitment to governance clear. Less than 15% of consumers say they know which companies protect their data the best. Startups can take advantage of this knowledge gap by adopting agile data governance and educate their customers about how to protect themselves in the risky world of the Third Wave.

Some incumbents may always be safe. But those in highly-regulated Third Wave industries, such as automotive, healthcare, and telecom should be worried; customers trust these incumbents the least. Startups that adopt agile data governance, however, will be trusted the most, and the time to act is now. 


TechCrunch

Fintech has been one of the bigger stories of the UK startup world — due in no small part to the fact that its capital, London, is also one of the world’s major financial centers. Today, one of those startups made a big splash by buying an incumbent business, and taking on an equity investment alongside that, to scale up its position in the market.

Jaja, a mobile-first business that provides digital and physical credit cards and other financing services, today announced that it will be acquiring the UK credit card accounts for an initial cash consideration of £530 million (or $ 671 million at current rates). It will also become the consumer credit card issuer for the Bank’s UK business and the AA. At the same time it’s also getting an equity investment of £20 million in its own business.

“This announcement with Bank of Ireland UK is an exciting and important development in Jaja’s journey and is part of our strategy to create partnerships that will help more people embrace a simpler way of managing credit,” said Neil Radley, CEO of Jaja Finance, in a statement. “Our vision is to enable a new generation of mobile-first credit card products with unrivalled functionality, service and security. We’re excited to be welcoming Bank of Ireland UK customers as cardholders.”

The Bank of Ireland’s UK credit business includes a number of key accounts covering the AA (UK’s Automobile Association), the Post Office, as well as a card branded Bank of Ireland itself. (It excludes the bank’s commercial card business in the Republic of Ireland.)

The Bank had put the business up for sale some time ago as part of a bigger strategy to divest of its capital-intensive, competitive operations in a push to grow profitability by improving its loans and mortgages business: amid that, the Bank’s wider UK business has been a challenge for it, with investors going so far as to value the UK business at zero earlier this month.

“Jaja is an innovative company which shares our commitment to delivering outstanding customer service. We are proud to partner with them and bring their next generation credit card to customers across the UK,” said Bank of Ireland UK CEO Des Crowley in a statement. “Today’s announcement demonstrates the Bank’s continued progress in delivering against its strategic targets for growth and transformation to 2021, as set out at its Investor Day in June 2018.”

Jaja’s deal is being done in partnership with KKR, Centerbridge Partners and other unnamed investors, who are helping finance the acquisition and are also putting £20 million ($ 25 million) of equity investment into Jaja (pronounced “yah-yah”) alongside it. Prior to this, Jaja had raised about about $ 16 million, including about £3 million by way of the Seedrs crowdfunding platform.

The company is not disclosing its valuation amid this $ 671 million purchase.

A spokesperson for Jaja said the startup is not releasing any numbers today that point to how much the company’s current services are being used. The company, which is today active only in the UK, has taken the route of keeping a waitlist to onboard new users, and it was reported to have some 6,000 people on it back in February just ahead of the Jaja launching its cards.

The company also has a deal with Asda, the UK business of Walmart, to provide financing at the point of sale for its online storefront George.com (an Amazon-type everything store akin to Walmart.com). Given that Jaja has up to now not operated on a massive scale — even if it took on its whole waitlist, that would only number 6,000 customers, for example — it’s likely that this latest acquisition will be adding a sizeable number of users, and key brands, into its stable in one fell swoop.

Jaja was founded by Jostein Svendsen, Kyrre Riksen and Per Elvebakk — London-based Norwegian entrepreneurs who have previously found and sold other financial and tech startups (Svenden, for example, sold a previous company to American Express) — and is currently led by CEO Neil Radley, who had previously been the MD for Barclaycard in Western Europe.

Its key mission has been to bring a more modern approach to the world of credit and credit cards. That in itself is not hugely unique — it is essentially the purpose of all consumer-facing credit startups today — but given that the vast majority of credit services, and transactions, are still handled through traditional channels, it’s disruptive nonetheless.

The company describes itself as digital, mobile-first business, which in its case means that you apply for and initiate services through the company’s app — using your phone’s camera to snap your ID and an AI-based algorithm that takes in other data about you to provide what Jaja describes as “near instant” credit decisions within minutes. Jaja provides physical cards (Visa is its credit card partner), but it also allows people to use the cards through their digital wallets immediately. The company does not change for foreign currency exchanges and offers free cash withdrawal fees, with an annual percentage rate (APR) of 18.9%. And in keeping with what is now par for the course for challenger fintech services, you can use the app to get real-time updates on your account, modify repayments and more.

On that note, in addition to the challenge of onboarding a number of established brands and a large number of users on to a new platform that up to now has been adding users intentionally slowly, it will be interesting to see how and if Jaja can inject more modern infrastructure into those established operations, and a customer base that’s used to the traditional way of doing things. For now, it says that customers of those services will continue to use them as they have done.


TechCrunch

After a Wall Street Journal investigation concluded that there are millions of fake business listings on Google Maps, the company has issued a response detailing the measures it takes to combat the problem.

According to estimates from online advertising experts surveyed by the WSJ, there are “roughly 11 million falsely listed businesses on any given day,” with hundreds of thousands more fake listings appearing every month. Many are placed by businesses that specialized creating fake listings for clients that want to boost their information above competitors in search results.

According to a search expert interviewed by the WSJ, a 2017 academic study paid for by Google that found only 0.5% of local searches researchers examined were fake was skewed by limited data.

In the company’s response, Google Maps product director Ethan Russell wrote that of the more than 200 million listings added to Google Maps over the years, only a “small percentage” are fake. He said that last year Google took down more than 3 million fake business profiles, including more than 90% that were removed before users could see them. Google’s systems identified 85% of the listings removed, while 250,000 were reported by users. The company also disabled 150,000 user accounts found to be abusive, a 50% increase from 2017.

Russell wrote that the company is “continually working on new and better ways to fight these scams using a variety of ever-evolving manual and automated systems,” but can’t share more details about them because otherwise scammers might find a way to get around them.

The WSJ report comes as another Google-owned service, YouTube, is under scrutiny for how it fights abuse at scale. YouTube released its first anti-abuse report last year, but problematic content, including hate speech, continues to be a major problem and the platform’s critics say it haphazardly enforces its own policies.

Along with Apple, Amazon and Facebook, Google’s parent company Alphabet is currently facing antitrust investigations by the Federal Trade Commission and Justice Department, and its search business is expected to go under scrutiny.


TechCrunch

Low code and no code are the latest industry buzzwords, but if vendors can truly abstract away the complexity of difficult tasks like building machine learning models, it could help mainstream technologies that are currently out of reach of most business users. That’s precisely what Microsoft is aiming to do with its latest Power BI platform announcements today.

The company tried to bring that low code simplicity to building applications last year when it announced PowerApps. Now it believes by combining PowerApps with Microsoft Flow and its new AI Builder tool, it can allow folks building apps with PowerApps to add a layer of intelligence very quickly.

It starts with having access to data sources, and the Data Connector tool gives users access to over 250 data connectors. That includes Salesforce, Oracle and Adobe, as well as of course Microsoft services like Office 365 and Dynamics 365. Richard Riley, senior director for Power Platform marketing, says this is the foundation for pulling data into AI Builder.

“AI Builder is all about making it just as easy in a low code, no code way to go bring artificial intelligence and machine learning into your Power Apps, into Microsoft Flow, into the Common Data Service, into your data connectors, and so on,” Riley told TechCrunch.

Screenshot: Microsoft

Charles Lamanna, general manager at Microsoft says that Microsoft can do all the analysis and heavy lifting required to build a data model for you, removing a huge barrier to entry for business users. “The basic idea is that you can select any field in the Common Data Service and just say, ‘I want to predict this field.’  Then we’ll actually go look at historical records for that same table or entity to go predict [the results],” he explained. This could be used to predict if a customer will sign up for a credit card, if a customer is likely to churn, or if a loan would be approved, and so forth.

While Microsoft admits this won’t be something everyone uses, they do see a kind of power user who might have been previously unable to approach this level of sophistication on their own, building apps and adding layers of intelligence without a heck of a lot of coding. If it works as advertised it will bring a level of simplicity to tasks that were previously well out of reach of business users without requiring a data scientist.


TechCrunch

More than three years ago, self-driving trucks startup Starsky Robotics was founded to solve a fundamental issue with freight — a solution that CEO Stefan Seltz-Axmacher believes hinges on getting the human driver out from behind the wheel.

But a funny thing happened along the way. Starsky Robotics started a regular ol’ trucking company. Now, nearly half of the employees at this self-driving truck startup help run a business that uses the traditional model of employing human drivers to haul loads for customers, TechCrunch has learned.

Starsky’s trucking business, which has been operating in secret for nearly two years alongside the company’s more public pursuit of developing autonomous vehicle technology, has hauled 2,200 loads for customers. The company has 36 regular trucks that only use human drivers to haul freight. It has three autonomous trucks that are driven and supported by a handful of test drivers. Starsky also employs a number of office people who, as Seltz-Axmacher notes, “know how to run trucks.”

The CEO and co-founder contends that without the human-driven trucking piece, Starsky won’t ever have an operational, or profitable, self-driving truck business. The trucking business has generated revenue, led to key partnerships such as Schneider Logistics, Penske and Transport Enterprise Leasing, and importantly, helped build a company that works in the real world. It has also been a critical tool for recruiting and vetting safety drivers and teleoperators (or remote drivers), according to Seltz-Axmacher.

“The decision to have a trucking business interact with the real trucking world in parallel with developing the robotics piece is a necessary part of building a longstanding business in the space,” said Reilly Brennan, general partner at Trucks VC and the first institutional investor in Starsky.

Starksy, which was co-founded by Seltz-Axmacher and Kartik Tiwari, has raised $ 21.7 million in equity from investors including Shasta Ventures and Trucks VC.

The evolution over at Starsky illustrates the challenge that awaits the autonomous vehicle industry and the giant companies and startups operating within it. Even after engineers solve the complexity of building an AI-powered driver that’s better than a human, these companies must figure out the equally intricate task of operations. Robotaxis, autonomous delivery robots and self-driving trucks won’t matter if humans don’t use, like or trust the tech.

Figuring out the basics of operations — including the rather pedestrian and obvious ones — will mean the difference between making or losing money. Or, having a business at all.

And the stakes are high. Trucks are the backbone of the U.S. economy and moved more than 70% of all U.S. freight and generated more than $ 700 billion in 2017, according to the most up-to-date statistics available from the American Trucking Associations (ATA).

Companies pursuing robotaxis and other autonomous vehicle programs are going to eventually wake up — if they haven’t already — to the same realities that Starsky has accepted, Brennan contends.

“The interaction with the market, particularly in logistics, is vital,” Brennan said, adding that companies pursuing robotaxis that haven’t built out and tested a consumer-facing app risk the same problems. “They need to have a business on day one, not on day 720.”

For Starsky, it started with something as basic as having a working vehicle and access to mechanics that could fix it.

Trucks, the hard way

Seltz-Axmacher admits now he underestimated how difficult trucks could be.

“Hey, it’s a truck, how hard can buying one be?,” said Seltz-Axmacher, as he described the company’s first major purchase of a truck for about $ 50,000. “We quickly realized that having a truck and driving a truck are not easy things to do.”

Starsky engineers retrofitted the truck, named Rosebud, with its autonomous driving system and made plans to test it at the Thunderhill Raceway about 150 miles north of San Francisco. It didn’t make it. The truck’s engine was smoking by the time it crossed the Bay Bridge. And then the truck, along with all those engineers, sat for two weeks while Seltz-Axmacher hunted for a diesel mechanic.

Self-driving truck startup Starsky Robotics began with this first, and problematic truck

The truck, pictured above, continued to break down. The company ran into more snafus, including a problem with insurance and the title of the vehicle. Starsky was going to miss a key milestone and Seltz-Axmacher was going to have to tell investors that it wasn’t because of bottlenecks in engineering, but because they didn’t know how to manage the truck part of this self-driving truck company.

The founders learned that even “average” trucks needed to go to the shop every 60 days, which is operationally complex when vehicles are traveling throughout the United States.

Starsky ended up making a key hire, Paul Schlegel, who is a veteran of trucking operations, to organize the enterprise. Schlegel, who has 32 years in the transportation industry with companies such as Schneider National and Stevens Transport, developed the trucking business that enabled autonomous trucks, but still worked in their absence. The trucking operations team is in Dallas. 

The driver pinchpoint

Seltz-Axmacher has said repeatedly that “unless you’re getting the driver out of the truck, you’re not solving anything.”

The problem in trucking is the supply of drivers. The chronic shortage has, in turn, driven up costs. For instance, the median salary for a truckload driver working a national, irregular route was more than $ 53,000 — a $ 7,000 increase from ATA’s last survey, which covered annual pay for 2013, or an increase of 15%. It’s even higher for private fleet drivers, who saw their pay rise to more than $ 86,000 from $ 73,000, or a gain of nearly 18%.

Starksy soon found that finding the right drivers was just as hard as finding the right trucks. The Federal Motor Carrier Safety Administration shows the company has reported three crashes of its manually driven trucks.

Seltz-Axmacher said they’ve had a driver make a wrong turn and have a low-hanging branch rip a hole in the side of a trailer. The most serious incident involved a new driver who took an offramp in Florida too fast and rolled the truck onto its side. No one was injured and the driver was terminated.

These drivers are critical to the autonomous program and the best of them end up becoming teleop controllers, a job that involves sitting in an office, not logging days and weeks in a truck.

Starsky is taking a dual approach to its autonomous trucks. It outfits regular trucks with a combination of sensors like radar and cameras along with software that allows long-haul trucks to drive autonomously on the highway. When the truck is about to exit, a trained remote operator, who is sitting in an office, takes over and navigates the truck to its final destination.

The promise of being able to be promoted to teleoperator is a big part of how Starsky is able to hire drivers effectively. The company contends it wouldn’t be possible to find 25 highly skilled safety and remote drivers without having a broader fleet of regular truck drivers to choose from.

Robotrucks or bust

The ultimate goal of Starsky Robotics hasn’t changed, Seltz-Axmacher said. To get there, the company recently hired Ain McKendrick as vice president of engineering, and former Tesla executive Keith Flynn to head up its hardware manufacturing to support Starsky’s fleet build. McKendrick, who co-founded Podtek and Lyve, also has experience at autonomous vehicle company Cyngn, Highfive, Netflix and Dell .

By early 2020, the company aims to have 25 autonomous trucks — a goal that is only possible if it has 100 regular trucks, he added.

The only way Starsky can scale its operations on the autonomous side is to continue to scale its regular trucking operations six months in advance. In other words, the regular trucking business is inextricably linked to the success of deploying autonomous trucks.

The company has already found that the 15-plus brokers that are regularly giving it freight to haul are ready for driverless trucks.

“Many times the brokers who have given us loads have been fairly ambivalent to whether or not we’re hauling that freight with a self-driving truck, Seltz-Axmacher said. “A lot of the concern that people might have is that this is a technology-averse industry and might not be willing to accept self-driving trucks has proven not to be true.”


TechCrunch

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